Large language models (LLMs) developed, deployed, and researched across the GCC — including Falcon (TII), Jais (MBZUAI/Inception), AceGPT (KAUST), ALLaM (SDAIA), and Fanar (QCRI).
The UAE has launched a new guide focusing on generative AI, aimed at accelerating the adoption of these advanced technologies across its government and business sectors. This initiative seeks to integrate AI tools and frameworks to enhance operational efficiencies and foster innovation. The guide likely provides strategic direction and best practices for the responsible and effective deployment of generative AI solutions nationwide. Why it matters: This national policy underscores the UAE's proactive strategy to solidify its position as a global leader in AI adoption and leverage cutting-edge technologies for economic growth and digital transformation.
The UAE has reportedly released a new guide focused on generative AI, aiming to accelerate its adoption across both government entities and private businesses. This initiative outlines strategies and frameworks for integrating advanced AI technologies into various sectors. The guide is designed to foster innovation and enhance efficiency throughout the UAE's economy. Why it matters: This development underscores the UAE's strategic commitment to establishing itself as a global leader in AI development and deployment, driving digital transformation and economic competitiveness.
The UAE has received its initial shipment of advanced AI chips from Nvidia, marking a significant milestone in its national AI strategy. These chips are essential for powering the country's growing supercomputing capabilities and accelerating the development of large language models. This delivery underscores the UAE's commitment to establishing itself as a global leader in AI innovation. Why it matters: This acquisition directly enhances the UAE's capacity for advanced AI research and development, solidifying its competitive position in the global AI landscape and fostering local technological growth.
G42, a prominent UAE-based AI technology holding company, has launched a new sovereign enterprise AI assistant. This product is designed to offer secure, localized AI capabilities for businesses and government entities within the region. It aims to prioritize data privacy and cater to the specific regional context, expanding G42's offerings in specialized enterprise solutions. Why it matters: This launch underscores the UAE's strategic drive to develop secure, locally-controlled AI solutions for critical sectors, thereby bolstering its digital sovereignty and reducing reliance on external AI infrastructure.
A unit of UAE's G42 has launched a new 'sovereign enterprise AI assistant' aimed at supporting businesses with secure, localized artificial intelligence solutions. This product is designed to offer robust AI capabilities while maintaining data sovereignty and control for enterprises. The launch signifies G42's continued expansion into the enterprise AI market within the UAE and the broader region. Why it matters: This initiative reinforces the UAE's commitment to developing secure, in-country AI capabilities, enhancing operational efficiency for regional enterprises, and fostering data sovereignty.
The UAE government has announced an ambitious target to integrate Agentic AI into 50% of its federal government services within the next year. This initiative aims to enhance efficiency, personalize citizen interactions, and streamline government operations across various sectors. It involves deploying autonomous AI agents capable of handling tasks, responding to inquiries, and automating service delivery. Why it matters: This ambitious target positions the UAE as a global leader in AI governance and public service automation, potentially setting a precedent for other nations.
Technology Innovation Institute (TII) won the UAE AI Award for Emirati AI Solutions for its Falcon LLM series. AI71 also won for LAW71, an AI-powered legal solution, and RAZI71, an AI-powered healthcare solution. The award recognizes AI innovations made in the UAE that demonstrate innovation, AI ethics compliance, maturity, and scalability. Why it matters: The award highlights the UAE's commitment to developing local AI talent and solutions, particularly in open-source models, for global collaboration and positive transformation.
The Technology Innovation Institute (TII) in Abu Dhabi has launched the Falcon Foundation, a non-profit dedicated to advancing open-source generative AI models. TII is committing $300 million to fund open-source AI projects, beginning with its Falcon AI models. The foundation aims to foster collaboration among stakeholders, developers, academia, and industry to promote transparent governance and knowledge exchange in AI. Why it matters: This initiative signals the UAE's commitment to leading in AI development through open-source innovation and collaboration, potentially accelerating AI adoption and customization across various sectors.
Abu Dhabi's Advanced Technology Research Council (ATRC) has launched AI71, a new AI company building on the Falcon generative AI models developed by TII. AI71 will focus on multi-domain specializations, offering AI data control options for companies and countries looking to self-host for greater privacy. The company will be taken to market by ATRC's VentureOne subsidiary, initially targeting the medical, educational, and legal sectors. Why it matters: AI71 aims to establish Abu Dhabi and the UAE as a major AI player by providing decentralized data ownership and promoting broader access to AI technology.
Technology Innovation Institute (TII) in the UAE has launched Falcon 180B, an open access large language model with 180 billion parameters trained on 3.5 trillion tokens. Falcon 180B ranks first on the Hugging Face Leaderboard for pretrained LLMs, outperforming Meta's LLaMA 2 and nearing the performance of OpenAI's GPT-4 and Google's PaLM 2. The model is available for research and commercial use under the 'Falcon 180B TII License', based upon Apache 2.0. Why it matters: This release strengthens the UAE's position in AI development and promotes open access to advanced AI technology, fostering innovation and collaboration.
TII's Falcon 40B, a 40-billion-parameter open-source AI model, has ranked #1 on Hugging Face's Open LLM Leaderboard, surpassing models like LLaMA and StableLM. The leaderboard uses benchmarks like AI2 Reasoning Challenge, HellaSwag, MMLU, and TruthfulQA. Trained on one trillion tokens, Falcon 40B's weights are available for research and commercial use. Why it matters: This achievement positions the UAE as a leader in generative AI and promotes transparent, inclusive AI development.
Saudi Arabia’s HUMAIN, an investment firm, has invested $3 billion in xAI's Series E funding round. This investment precedes xAI's anticipated acquisition by SpaceX. The funding will support xAI's endeavors in infrastructure development and advanced technologies. Why it matters: This marks a significant commitment from Saudi Arabia towards AI infrastructure, potentially fostering further technological advancements in the region.
KAUST has unveiled Shaheen III, the most powerful supercomputer in the Middle East and 18th globally, built by HPE. The system uses 2,800 NVIDIA GH200 Grace Hopper Superchips, tripling the processing power of its predecessor. Shaheen III will support research in Arabic LLMs, climate modeling, remote sensing, automated chemistry, and AI-driven healthcare. Why it matters: This infrastructure investment strengthens Saudi Arabia's position in AI and computational research, enabling advances tailored to the region's needs and priorities.
UAE President Sheikh Mohamed bin Zayed Al Nahyan met with OpenAI CEO Sam Altman to discuss cooperation in advanced technology, particularly AI. The meeting focused on leveraging AI to accelerate development and benefit humanity. This high-level discussion underscores the UAE's strategic commitment to becoming a global leader in AI innovation. Why it matters: This direct engagement between the head of state and a leading AI figure signals the UAE's intent to forge top-tier partnerships and influence the future direction of AI development on a national and global scale.
President Sheikh Mohamed bin Zayed Al Nahyan of the UAE received Sam Altman, the CEO of OpenAI. The high-level meeting likely focused on strategic discussions regarding artificial intelligence development and collaboration. This engagement highlights the UAE's proactive approach to integrating advanced AI technologies into its national agenda. Why it matters: Interactions between national leaders and prominent AI industry figures often signal future policy directions, potential investments, and significant technological partnerships for the region.
The UAE President has endorsed the launch of K2 Think, which is described as the world’s most advanced open-source reasoning model. This launch recognizes Sheikh Khalifa’s contributions to advancing science and technology within the UAE. The announcement signifies a major national initiative in the field of artificial intelligence development. Why it matters: This positions the UAE at the forefront of open-source AI innovation and advanced reasoning capabilities, potentially setting new benchmarks for global AI development.
Saudi Arabia is collaborating with NVIDIA to develop and build 'AI factories' within the Kingdom. These 'AI factories' will accelerate the development and deployment of generative AI and other advanced AI applications, providing powerful computing infrastructure. The initiative aims to support Saudi Arabia's vision of becoming a global leader in AI development, enabling what NVIDIA terms the 'Age of Reasoning.' Why it matters: This major strategic partnership signifies Saudi Arabia's significant investment in advanced AI infrastructure, positioning the Kingdom as a key player in the global AI landscape and fostering domestic AI innovation.
Inception, a G42 company, has launched InceptionClaw, an enterprise-grade AI super assistant designed for enterprise leaders and government officials. Built on Inception's Catalyst platform and powered by Compass models, InceptionClaw actively manages workloads by monitoring calendars and emails, delivering structured briefs, alerts, and audio summaries. It operates with UAE-native sovereignty, ensuring all data remains within UAE jurisdiction under Greenshield sovereign controls, addressing critical data residency and trust requirements. The assistant also includes features like tamper-proof audit trails, code-reviewed skills, spending limits, and human approval queues for high-stakes actions.
G42, a global leader in artificial intelligence based in Abu Dhabi, partnered with creative innovation company R/GA to launch alpha.G42.ai, a generative interface designed to transform traditional websites into dynamic, conversational systems. This prototype redefines a brand's digital presence by employing an intelligent agent powered by integrated large language models (LLMs) to generate and curate personalized content for each visitor in real-time. The system processes various content types as knowledge, which it then synthesizes to produce dynamic, tailored outputs for users interacting via voice or text, moving beyond static content management. Why it matters: This initiative from a major UAE AI firm pioneers a novel approach to web interfaces, potentially influencing future digital interactions and content delivery globally.
Yasi One, a new artificial intelligence system, has been launched from Abu Dhabi, UAE. This AI is specifically noted for its unique capability to 'think before it responds,' suggesting advanced processing and reasoning functionalities. The launch of Yasi One was reported by Gulf News. Why it matters: This development underscores Abu Dhabi's growing ambition to develop and deploy cutting-edge AI technologies, potentially contributing to more sophisticated and contextually aware AI applications in the region.
This study introduces a Probabilistic Graphical Model (PGM) framework utilizing Pearl's do-operator to causally audit LLM safety mechanisms, specifically isolating the effect of injecting cultural demographics into prompts. A large-scale empirical analysis was conducted across seven instruction-tuned models from diverse origins, including the UAE's Falcon3-7B, as well as models from the US, Europe, China, and India, using ToxiGen and BOLD datasets. The findings revealed a disparity between observational and interventional bias, demonstrating that standard fairness metrics can overestimate demographic bias. Western models exhibited higher causal refusal rates for specific demographic groups, while Eastern models showed low overall intervention rates with targeted sensitivities toward regional demographics. Why it matters: This research highlights the geopolitical nuances of LLM safety alignment and the potential for demographic-sensitive over-triggering to restrict benign discourse, which is particularly relevant for diverse regions like the Middle East in developing culturally-aware AI.
Researchers from MBZUAI have proposed the Cylindrical Representation Hypothesis (CRH) to explain the instability and unpredictability observed in large language model steering. CRH relaxes the orthogonality assumption of the existing Linear Representation Hypothesis, positing a cylindrical structure where a central axis captures concept differences and a surrounding normal plane controls steering sensitivity. The hypothesis suggests that the intrinsic uncertainty in identifying specific sensitive sectors within this normal plane accounts for why steering outcomes frequently fluctuate even with well-aligned directions. Why it matters: This research offers a more robust theoretical framework for understanding and potentially improving the control and reliability of large language models.
Researchers at MBZUAI have developed a new method for controllable poetry generation in Arabic and its dialects, moving beyond traditional analysis tasks for Arabic poetry within Large Language Models (LLMs). They introduce a large-scale, instruction-based dataset in Modern Standard Arabic (MSA) and various Arabic dialects, enabling LLMs to perform tasks like writing, revising, and continuing poems based on user criteria. Experiments show that fine-tuning LLMs on this dataset results in models capable of generating poetry aligned with user requirements, validated by automated metrics and human evaluation. Why it matters: This work represents a significant advancement in Arabic Natural Language Processing, offering tools for creative expression and cultural preservation while opening new avenues for user-guided content generation in culturally rich text forms.
Agentic AI is set to be integrated into UAE government services, indicating a shift in how residents will interact with public sector offerings. This initiative aims to leverage advanced AI capabilities to transform government operations and service delivery. The changes are expected to impact various aspects of resident engagement with government platforms. Why it matters: This move signifies a major step in the UAE's strategy to modernize its public services through cutting-edge AI, potentially setting a new standard for citizen-centric digital governance in the region.
Google has introduced a new AI feature in the United Arab Emirates, designed to provide more intelligent and personalized answers to users. This feature reportedly leverages user data, with consent, to enhance its responsiveness and relevance. The rollout in the UAE signifies the expansion of Google's advanced AI services into the Middle East market. Why it matters: This launch represents increased access to sophisticated AI tools for consumers and businesses in the UAE, potentially accelerating AI adoption and innovation in the local digital economy.
Researchers proposed a severity-aware weighted loss method to fine-tune Arabic language models for medical text generation, prioritizing severe clinical cases. This approach utilizes soft severity probabilities, derived from an AraBERT-based classifier, to dynamically scale token-level loss contributions during optimization on the MAQA dataset. The method consistently improved performance across ten Arabic LLMs, with AraGPT2-Base increasing from 54.04% to 66.14% and AraGPT2-Medium from 59.16% to 67.18%. Why it matters: This novel fine-tuning strategy addresses a critical limitation in medical AI by enhancing the safety and reliability of Arabic medical large language models, particularly in high-stakes clinical scenarios.
Arabic-DeepSeek-R1 is an application-driven, open-source Arabic Large Language Model (LLM) that has achieved a new state-of-the-art (SOTA) across the Open Arabic LLM Leaderboard (OALL). The model utilizes a sparse Mixture-of-Experts (MoE) backbone and a four-phase Chain-of-Thought (CoT) distillation scheme, which incorporates Arabic-specific linguistic verification and regional ethical norms. It records the highest average score on the OALL suite and outperforms proprietary frontier systems like GPT-5.1 on a majority of benchmarks evaluating comprehensive Arabic language-specific tasks. Why it matters: This work offers a validated and cost-effective framework for developing high-performing, culturally-grounded AI for under-represented languages, addressing the digital equity gap.
Researchers have developed OmniScore, a family of deterministic learned metrics designed to evaluate generative text as an alternative to Large Language Models (LLMs) used as judges. OmniScore leverages small parameter models (<1B) and was trained on approximately 564,000 synthetic instances across 107 languages, then evaluated using 8,617 manually annotated instances. It approximates LLM-judge behavior while offering low latency and consistency for various evaluation settings like reference-based and source-grounded assessments in tasks like QA, translation, and summarization. Why it matters: This development provides a practical, scalable, and reproducible method for multilingual generative text evaluation, addressing key limitations of LLM-as-a-judge approaches and offering significant benefits for AI development in linguistically diverse regions.
QIMMA is introduced as a quality-assured Arabic LLM leaderboard that places systematic benchmark validation at its core. It employs a multi-model assessment pipeline combining automated LLM judgment with human review to identify and resolve quality issues in established Arabic benchmarks. The resulting evaluation suite comprises over 52,000 samples, predominantly grounded in native Arabic content, with transparent implementation via LightEval and EvalPlus. Why it matters: This initiative provides a more reliable and reproducible foundation for evaluating Arabic Large Language Models, addressing critical quality concerns in existing benchmarks.
Researchers from MBZUAI have introduced WR-Arena, a new comprehensive benchmark designed to evaluate World Models (WMs) beyond traditional next-state prediction and visual fidelity. WR-Arena assesses WMs across three core dimensions: Action Simulation Fidelity, Long-horizon Forecast, and Simulative Reasoning and Planning, using a curated task taxonomy and diverse datasets. Extensive experiments with state-of-the-art WMs revealed a significant gap between current models' capabilities and human-level hypothetical reasoning. Why it matters: This benchmark provides a critical diagnostic tool and guideline for developing more robust and intelligent world models capable of advanced understanding, forecasting, and purposeful action, particularly for AI research in the region.
The UAE's extensive utilization of American Graphics Processing Units (GPUs) for its artificial intelligence development has established US technology as a "dominant standard" in the region. This observation was made by Michael Kratsios, former US Chief Technology Officer and AI adviser to Donald Trump. The reliance highlights the critical role of hardware supply chains in shaping global AI capabilities. Why it matters: This underscores the geopolitical implications of technological dependency and the strategic advantage held by nations controlling essential AI infrastructure.
Researchers developed a retrieval-augmented generation (RAG) framework to improve Arabic Large Language Models (LLMs) in understanding complex historical and religious texts like the Quran and Hadith. This framework grounds LLMs in the Doha Historical Dictionary of Arabic (DHDA) through hybrid retrieval and intent-based routing. The approach significantly boosted the accuracy of Arabic-native LLMs such as Fanar and ALLaM to over 85%, closing the performance gap with proprietary models like Gemini. Why it matters: This research offers a novel method for enhancing Arabic NLP capabilities for historically nuanced texts, demonstrating the value of integrating diachronic lexicographic resources into RAG systems for deeper language understanding.
A new approach to composed video retrieval (CoVR) is presented, which leverages large multimodal models to infer causal and temporal consequences implied by an edit. The method aligns reasoned queries to candidate videos without task-specific finetuning. A new benchmark, CoVR-Reason, is introduced to evaluate reasoning in CoVR.
Hamad Bin Khalifa University (HBKU) has released Fanar 2.0, the second generation of Qatar's Arabic-centric Generative AI platform, built entirely at QCRI. The core of Fanar 2.0 is Fanar-27B, which was continually pre-trained from a Gemma-3-27B backbone using 120 billion high-quality tokens and only 256 NVIDIA H100 GPUs. Fanar 2.0 includes capabilities like FanarGuard, Aura, Oryx, Fanar-Sadiq, Fanar-Diwan, and FanarShaheen for moderation, speech recognition, vision understanding, Islamic content, poetry generation, and translation. Why it matters: This shows that sovereign, resource-constrained AI development in the Arabic language is possible, producing competitive systems in the region.
Technology Innovation Institute (TII) and Mila, the Quebec AI Institute, announced a strategic partnership to collaborate on AI safety and next-generation machine learning models. TII will establish a research lab at Mila in Montreal, enabling collaboration between UAE-based researchers and Mila's AI specialists. The partnership aims to translate scientific advances into real-world impact and strengthen the global research ecosystem. Why it matters: This collaboration enhances UAE-Canada scientific ties, positioning both communities for breakthroughs in areas like LLMs and AI safety, aligning with the UAE's vision to become a global AI research hub.
Technology Innovation Institute (TII) will make its Falcon-H1 large language model available as an NVIDIA NIM microservice. Falcon-H1 features a hybrid Transformer–Mamba architecture supporting context windows of up to 256k tokens. The model's availability on NVIDIA NIM aims to provide enterprises with a plug-and-play asset for building AI systems. Why it matters: This integration will simplify deployment and scaling of Falcon-H1 for enterprises, potentially accelerating the adoption of sovereign AI solutions in the region.
Technology Innovation Institute (TII) and AI71 are collaborating with Amazon Web Services (AWS) to expand global access to TII’s Falcon models and AI71’s enterprise AI products. TII already offers Falcon LLMs through Amazon SageMaker, and new models will be available via Amazon Bedrock. AI71’s products are already available in the AWS Marketplace, providing access for millions of customers globally. Why it matters: This partnership enhances the accessibility of UAE-developed AI technologies and strengthens the UAE's position as a leader in AI innovation by leveraging AWS's global infrastructure and customer base.
TII in Abu Dhabi has launched Falcon Arabic, the first Arabic language model in the Falcon series, which is now the best-performing Arabic AI model in the region. They also released Falcon H1, a new model designed for performance and portability, outperforming Meta’s LLaMA and Alibaba’s Qwen in the small-to-medium size category. Falcon Arabic is built on Falcon 3-7B and trained on a high-quality native Arabic dataset. Why it matters: These releases strengthen the UAE's position as a leader in Arabic language AI and democratize access to high-performance AI models.
The Technology Innovation Institute (TII) in Abu Dhabi has launched Falcon 3, a new series of open-source large language models. Falcon 3 models range in size from 1B to 10B parameters and have been trained on 14 trillion tokens. Falcon 3 achieved the top spot on Hugging Face's LLM leaderboard for models under 13 billion parameters. Why it matters: This release democratizes access to high-performance AI by enabling efficient operation on laptops and light infrastructure, solidifying the UAE's position as a leader in open-source AI development.
H.E. Faisal Al Bannai, Secretary General of the Advanced Technology Research Council (ATRC), has been named one of TIME's 100 most influential people in AI. Al Bannai's leadership at ATRC has driven AI advancements through the Falcon LLM series developed by TII and the launch of AI71, which delivers AI solutions across sectors like medicine and education. This recognition reflects the UAE’s commitment to using AI for global good. Why it matters: The award highlights the UAE's growing prominence and strategic vision in shaping the global AI landscape, particularly through open-source initiatives.
Technology Innovation Institute (TII) has released Falcon Mamba 7B, a new large language model and the first State Space Language Model (SSLM) in its Falcon series. Falcon Mamba 7B is the top-ranked open-source SSLM globally, outperforming Meta's Llama 3.1 8B, Llama 3 8B, and Mistral’s 7B on HuggingFace benchmarks. SSLMs excel at understanding complex, evolving situations and have applications in NLP tasks like machine translation and text summarization. Why it matters: This release strengthens the UAE's position as an AI hub, demonstrating TII's commitment to pioneering research and open-source AI development in the region.
The Open Arabic LLM Leaderboard (OALL) has been launched to benchmark Arabic language models, addressing the gap in resources for non-English NLP. It incorporates datasets like AlGhafa, ACVA, and translated versions of MMLU and EXAMS from the AceGPT suite. The leaderboard uses normalized log likelihood accuracy for tasks, built around HuggingFace’s LightEval framework. Why it matters: This initiative promotes research and development in Arabic NLP, serving over 380 million Arabic speakers by enhancing the evaluation and improvement of Arabic LLMs.
The Technology Innovation Institute (TII) in Abu Dhabi has launched Falcon 2, a new series of large language models including the Falcon 2 11B and Falcon 2 11B VLM. The Falcon 2 11B outperforms Meta’s Llama 3 (8B) and performs on par with Google’s Gemma 7B, as verified by Hugging Face. Falcon 2 11B VLM is TII's first multimodal model with vision-to-language capabilities and is open-source, making it accessible to developers. Why it matters: This release strengthens the UAE's position in AI research and development, providing open-source models that can be deployed on smaller infrastructures and used in diverse sectors.
Abu Dhabi's Technology Innovation Institute (TII) is offering training compute power to scientists, researchers, and SME entrepreneurs with innovative use cases for Falcon 40B, its open-source LLM. TII is welcoming submissions globally across industries like biotech, engineering, finance, and healthcare. A dedicated AI Cross-Center Unit (AICCU) of over 40 AI scientists will assess proposals based on research objectives, methodology, and potential impact. Why it matters: This initiative can foster innovation in AI applications across various sectors by providing access to cutting-edge LLMs and substantial compute resources.
The Technology Innovation Institute (TII) in the UAE has made its Falcon 40B large language model royalty-free for commercial and research use. Falcon 40B is ranked #1 on Hugging Face's leaderboard for LLMs, outperforming models like LLaMA. The model is now available under the Apache 2.0 license, promoting open access and collaboration in AI. Why it matters: This decision could accelerate AI innovation in the region by providing easier access to a state-of-the-art LLM for both public and private sector applications.
The Technology Innovation Institute (TII) in Abu Dhabi has launched Falcon 40B, a 40-billion parameter large language model, as open source for research and commercial use. Falcon 40B was trained on one trillion tokens. TII is offering access to the model's weights and compute power for selected research proposals via VentureOne. Why it matters: This open-source release with commercial licensing disrupts LLM access in the region, fostering AI innovation and enabling diverse applications across sectors.
The Technology Innovation Institute (TII) in Abu Dhabi has launched Falcon LLM, a 40 billion parameter large language model (LLM). Developed by the AI and Digital Science Research Center (AIDRC), Falcon LLM outperforms GPT-3 while using less training compute. The model was trained on one trillion tokens and will impact fields like education and healthcare. Why it matters: This release establishes the UAE as a major player in generative AI and supports the nation's AI strategy.
Technology Innovation Institute (TII) in Abu Dhabi, in collaboration with LightOn, has launched NOOR, a 10 billion parameter Arabic natural language processing (NLP) model. The model was trained on a large, high-quality cross-domain Arabic dataset including web data, books, poetry, news, and technical information. It enables applications in automated summarization, chatbots, and personalized marketing. Why it matters: NOOR represents a significant advancement in Arabic NLP, potentially enabling more sophisticated AI applications tailored to the Arabic language and regional needs.
TII and LightOn have partnered to build the NOOR Platform for exascale computing, aimed at developing foundation models. The collaboration will leverage LightOn's expertise in large language models, with the first output being the largest Arabic language model to date. The platform will provide high-quality data pipelines and facilitate extreme-scale distributed training and serving. Why it matters: This partnership aims to establish Abu Dhabi as a center of AI excellence and boost the UAE's ambitions in high-tech innovation and NLP research.
Abu Dhabi’s Technology Innovation Institute (TII) has launched Falcon-H1 Arabic, a new large language model based on a hybrid Mamba-Transformer architecture. The Falcon-H1 family comes in 3B, 7B, and 34B parameter sizes and outperforms existing models on the Open Arabic LLM Leaderboard (OALL). The model features improvements in data quality, dialect coverage, and long-context stability. Why it matters: This release strengthens the UAE's position in Arabic AI and provides a high-performing model tailored to the linguistic and cultural needs of the region.